This project aims to predict the carbon intensity of electricity on a given grid using historical data.

• data/: Contains the dataset and preprocessed data files.
• models/: Contains the model definition and training scripts.
• venv/: Virtual environment directory.
• features.py: Defines the selected features.
• functions.py: Contains utility functions.
• main.py: Main entry point of the application.
• preprocessing.py: Handles data preprocessing.
• requirements.txt: Lists the dependencies.
• .gitignore: Specifies files to be ignored by Git.

1. Create Virtual Environment:

   python -m venv venv

2. Activate Virtual Environment:

   • On Windows:

     venv\Scripts\activate

   • On macOS/Linux:

     source venv/bin/activate

3. Install Dependencies:

   pip install -r requirements.txt

1. Preprocess the Data:

   python preprocessing.py

2. Train and Evaluate the Model:

   python models/model.py

This project is licensed under the MIT License - see the LICENSE file for details.